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Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...

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Updated: Nov 17, 2025

Identifying Protein-protein Interaction Sites Using Peptide Arrays

Identifying Protein-protein Interaction Sites Using Peptide Arrays

Published on: November 18, 2014

Reverse-Phase Protein Array: Technology, Application, Data Processing, and Integration.

Cristian Coarfa^1,2,3, Sandra L Grimm¹, Kimal Rajapakshe¹

¹Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA.

Journal of Biomolecular Techniques : JBT

|February 15, 2021

Summary

This summary is machine-generated.

Reverse-phase protein array (RPPA) is a high-throughput proteomics platform for quantifying proteins in many samples. This study details optimized protocols and software for RPPA in a core facility setting, enhancing cancer research.

Keywords:

post-translational protein array analysis proteomics software validation study

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Area of Science:

Proteomics and Bioinformatics
Cancer Biology
Biotechnology

Background:

High-throughput protein quantification is crucial for understanding complex biological systems, particularly in cancer.
Antibody-based platforms offer targeted detection of specific proteins and post-translational modifications.
Standardized protocols are essential for reproducible results in large-scale proteomic studies.

Purpose of the Study:

To describe optimized workflow protocols and software tools for Reverse-Phase Protein Array (RPPA) implementation in a core facility.
To present a robust RPPA platform capable of analyzing hundreds of proteins across thousands of samples.
To highlight the utility of RPPA for validation and discovery proteomic research in cancer biology.

Main Methods:

Robotic arraying of protein samples (lysates, serum, plasma) onto nitrocellulose-coated slides.
Antibody-based probing for total protein expression and post-translational modifications (e.g., phosphorylation).
Comprehensive workflow including sample prep, printing, labeling, scanning, image analysis, data normalization, QC, and statistical analysis.

Main Results:

Developed and optimized a complete RPPA workflow suitable for a core facility.
Current platform utilizes approximately 240 validated antibodies targeting key cancer-related signaling pathways.
Demonstrated the platform's robustness for analyzing large sample cohorts and integrating with other omics data.

Conclusions:

The described RPPA platform provides a valuable, high-throughput solution for targeted proteomics.
Optimized protocols and software ensure efficient and reliable data generation for cancer research.
RPPA is a powerful technology for both validating and discovering biological insights, especially when integrated with multi-omics data.